RNA Molecules Lives Are 10 Times Shorter Than Previously Thought

RNA molecules live an average of two minutes before they are eliminated by an exosome. (Image: University of Basel, Biozentrum)

A research group at the Biozentrum of the University of Basel has developed a new method to measure the half-life of RNA molecules. It was shown that standard methods yield distorted results and RNA molecules live on average only two minutes, ten times shorter than previously assumed. The results are now published in the scientific journal "Science Advances".

RNA molecules are single copies of the DNA of a cell. They transfer the genetic information of the DNA and serve as a template for the production of proteins that control all processes in the cell. These small information carriers are regulated over their lifetime, or rather half-life. After their production, RNA molecules serve as a template for protein production for a limited time before they are degraded.

So far, there have been two scientific methods used to measure the half-life of the RNAs. As Prof. Attila Becskei's research team at the Biozentrum, University of Basel, discovered, these conventional methods can be rather inaccurate and sometimes give inconsistent results. Becskei's team has now found a new way to show that RNA molecules do not live on average for 20 minutes, but only two minutes. "This was a challenging task for us because nobody knew in advance which method would deliver the right results," says Becskei.

The "Gene Control Method" shows: RNAs live briefly

The half-life of an RNA is relevant for scientific studies on the cell cycle. The whole process of cell division depends on the right amount of proteins to be available at the right time. If the concentrations in certain phases of the cell cycle do not match, errors occur.

The gene control method used by Becskei is already known, but has not hitherto been used to measure the half-life of RNA molecules. The reason for this is that complex gene techniques are necessary for this and it is protracted, since only one RNA can be examined at the same time. A single gene is regulated on the DNA so that the production of the RNA can be switched on and off. If RNA production is stopped, it is possible to measure how long the RNAs already produced in the cell persist. Thus, the lifetime of this RNA molecule can be determined. "So the method only yields the result for an RNA, the result is reliable," says Becskei.

The experiments were repeated for approximately 50 different genes and showed that 80% of all RNAs have a short lifetime and live less than 2 minutes. Only about 20 percent live longer, about 5 to 10 minutes. "These results are astonishing considering that it has previously been assumed that RNAs persist in the cell for an average of 20 minutes," says Becskei.

Conventional methods with hooks

So far, there have been essentially two main methods that scientists have used to measure the half-life of RNA molecules. In the transcriptional inhibition, a substance is administered to the cell which stops the production of the RNAs by all genes. "If, however, the production of all RNAs is stopped, other processes in the cell are also altered and they function. This distorts the results, "says Becskei.

The In Vivo label also has its shadow side: Here, the RNAs are first labeled and observed how long they persist in the cell. However, labeling with modified molecules can interfere with the function of the cell and lead to incorrect results. Thus, all methods used so far have a drawback since the measurement itself affects the processes to be measured. "It is hard to believe that scientists around the world knowingly work with methods that produce distorted results," says Becskei. "It seems that the philosopher and science theorist Paul Feyerabend was right: science is often quite anarchist."

The highest correlation was found between Becskei's method and a variant of the "in-vivo labelling" method. In most cases, both measures classified the same RNAs as stable and unstable, even if the average half-lives differ. Now the team would like to investigate in which areas the latter provides the right results and can be reliably deployed.

This article has been republished from materials provided by University of Basel. Note: material may have been edited for length and content. For further information, please contact the cited source.

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